Spatiotemporal monitoring of Bakhtegan Lake's areal fluctuations and an exploration of its future status by applying a cellular automata model
Recent developments of geospatial technologies and models have provided environmentalists and naturalists with a wide variety of facilities and approaches for improved monitoring and management of environmental resources. Rich temporal remote sensing datasets, e.g., Landsat imagery as well as geospa...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
13 February 2015
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| In: |
Computers & geosciences
Year: 2015, Jahrgang: 78, Pages: 37-43 |
| ISSN: | 0098-3004 |
| DOI: | 10.1016/j.cageo.2015.02.004 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.cageo.2015.02.004 Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S0098300415000266 
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| Verfasserangaben: | Taghi Jokar Arsanjani, Reza Javidan, Mohamad Jafar Nazemosadat, Jamal Jokar Arsanjani, Eric Vaz |
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| 245 | 1 | 0 | |a Spatiotemporal monitoring of Bakhtegan Lake's areal fluctuations and an exploration of its future status by applying a cellular automata model |c Taghi Jokar Arsanjani, Reza Javidan, Mohamad Jafar Nazemosadat, Jamal Jokar Arsanjani, Eric Vaz |
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| 520 | |a Recent developments of geospatial technologies and models have provided environmentalists and naturalists with a wide variety of facilities and approaches for improved monitoring and management of environmental resources. Rich temporal remote sensing datasets, e.g., Landsat imagery as well as geospatial modeling techniques, facilitate the process of monitoring and modeling environmental phenomena. The main objective of this paper is to monitor the spatiotemporal patterns of fluctuations of a dynamic lake in the south of Iran - Bakhtegan Lake - which has been influenced by extreme climate change conditions. To do so, a temporal coverage of 12 Landsat images from 1973 to 2013, was used to delineate the boundaries of the lake over time and analyze the occurred changes. Next, a cellular automata (CA) approach was adopted for simulating two main processes: ‘lake expansion’ and ‘lake shrinkage’. The CA model was then calibrated based on a statistical comparison of the simulated and actual images of one timestamp. Application of Kappa index analysis measures the performance of the model at a value of 83 percent. The calibrated CA model was then applied and the future status of the lake (by 2017) was modeled; this suggested a further 45 percent shrinkage in addition to its recent 42 percent shrinkage. In conclusion, the socio-ecological impacts and consequences of the lake's fluctuations are discussed in detail and some complementary recommendations are proposed. | ||
| 650 | 4 | |a Bakhtegan Lake | |
| 650 | 4 | |a Cellular automata | |
| 650 | 4 | |a Lake fluctuations | |
| 650 | 4 | |a Landsat images | |
| 650 | 4 | |a Spatiotemporal monitoring | |
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| 700 | 1 | |a Nazemosadat, Mohamad Jafar |e VerfasserIn |4 aut | |
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| 700 | 1 | |a Vaz, Eric de Noronha |e VerfasserIn |0 (DE-588)138670110 |0 (DE-627)604712006 |0 (DE-576)308528077 |4 aut | |
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